Classifying Variable Objects Using A Flexible Shape Model (1995)
| Citations: | 2 - 1 self |
BibTeX
@MISC{Lanitis95classifyingvariable,
author = {A. Lanitis and C.J. Taylor and T. Ahmed and T.F. Cootes and Tf. Cootes},
title = {Classifying Variable Objects Using A Flexible Shape Model},
year = {1995}
}
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Abstract
Point Distribution Models (PDMs) are statistical models which represent objects whose shape can vary. A useful feature of PDMs is their ability to capture the shape of variable objects within a training set with a small number of shape parameters. This compact and accurate parametrization can be used for the design of efficient classification systems. In this paper we describe a classification system which uses shape parameters. We have tested the system on classifying hand outlines, face outlines and hand gestures; experimental results are presented.
Citations
| 813 | Active shape models - their training and application - Cootes, Taylor, et al. - 1995 |
| 73 | A unified approach to coding and interpretting faces - Lanitis, Taylor, et al. - 1995 |
| 45 | BFJ: Multivariate Statistical Methods: a primer Third edition - Manly - 2005 |
| 7 | Automatic identification of human faces using flexible appearance models - Lanitis, Taylor - 1995 |
| 5 | Multi-Resolution Search using Active Shape Models - Cootes, Taylor, et al. - 1994 |
| 3 | A Model Based Hand Gesture Recognition System. Msc Thesis submitted to the - Ahmed - 1994 |
